Forest monitoring
Forest cover and loss as data: Global Forest Change, forest definitions and thresholds, rates, fragmentation, protected areas, hotspots, canopy height and new clearing.
Global Forest Change gives every 30-metre pixel on Earth a tree cover in 2000 and a year of loss since, and it has made forest statistics look easy. In a 3,000 km² window of Rondônia the headline is stark: 44% of the forest standing in 2000 was gone by 2024. Every word of that sentence is a decision — forest means canopy above 30%, the pixels are 0.00025° and shrink with latitude, loss means any stand-replacing event, and the figure belongs to one release of the data.
Change any of them and the number moves. A 10% threshold gives 41%, a 75% threshold 49%. The common "0.09 ha per pixel" overstates area by 19% at 10°S and 145% at 61°N. Protected land a kilometre inside the boundary lost 7.7% of its forest against 58% a kilometre outside, but comparing the two sides still mixes protection with access, and the boundary band made the estimate worse rather than better. A Sentinel-2 detector disagreed with the annual loss map almost entirely, because the two measured different intervals.
The concepts below settle what the data measures, how forest is defined, how rates, fragmentation and avoided loss are computed; the how-to guides work through real Hansen tiles, OSM protected areas and roads, H3 hotspots, land cover products, canopy height and Sentinel-2; and the fixes are the five ways forest numbers go wrong while looking authoritative.
🧭 Start with the concepts
The ideas the how-to guides below assume you already have.
- Global Forest Change Explained
- Forest Definitions Explained
- Deforestation Rates Explained
- Forest Fragmentation Explained
- Land Cover Products Explained
- Avoided Deforestation Explained
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⚙️ Then do the task
Step-by-step walkthroughs with code you can copy and adapt.
- How to Read Hansen Global Forest Change Data in Python
- How to Calculate Forest Loss by Year for a Region in Python
- How to Compare Forest Loss Inside and Outside Protected Areas in Python
- How to Measure Deforestation Near Roads in Python
- How to Measure Forest Fragmentation in Python
- How to Map Forest Loss Hotspots with H3 in Python
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🔧 When it breaks
The errors this topic produces, with the cause explained rather than just the command.
Learning paths through this topic
A curated route rather than a list — the guides in the order that builds on itself.
Related topics
Subjects that keep coming up alongside this one, most overlap first.